Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Dow University of Health Sciences, Karachi, Pakistan.
Int J Surg. 2023 Apr 1;109(4):946-952. doi: 10.1097/JS9.0000000000000285.
As artificial intelligence (AI)-assisted diagnosis gained immense popularity, it is imperative to consider its utility and efficiency in the early diagnosis of colorectal cancer (CRC), responsible for over 1.8 million cases and 881 000 deaths globally, as reported in 2018. Improved adenoma detection rate, as well as better characterizations of polyps, are significant advantages of AI-assisted colonoscopy (AIC). This systematic review (SR) investigates the effectiveness of AIC in the early diagnosis of CRC as compared to conventional colonoscopy.
Electronic databases such as PubMed/Medline, SCOPUS, and Web of Science were reviewed for original studies (randomized controlled trials, observational studies), SRs, and meta-analysis between 2017 and 2022 utilizing Medical Subject Headings terminology in a broad search strategy. All searches were performed and analyzed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis methodology and were conducted from November 2022. A data extraction form based on the Cochrane Consumers and Communication Review group's extraction template for quality assessment and evidence synthesis was used for data extraction. All included studies considered for bias and ethical criteria and provided valuable evidence to answer the research question.
The database search identified 218 studies, including 87 from PubMed, 60 from SCOPUS, and 71 from Web of Science databases. The retrieved studies from the databases were imported to Rayyan software and a duplicate article check was performed, all duplicate articles were removed after careful evaluation of the data. The abstract and full-text screening was performed in accordance with the following eligibility criteria: Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) for observational studies; Preferred Reporting Items for Systematic Reviews and Meta-Analysis for review articles, ENTREQ for narrative studies; and modified JADAD for randomized controlled trials. This yielded 15 studies that met the requirements for this SR and were finally included in the review.
AIC is a safe, highly effective screening tool that can increase the detection rate of adenomas, and polyps resulting in an early diagnosis of CRC in adults when compared to conventional colonoscopy. The results of this SR prompt further large-scale research to investigate the effectiveness in accordance with sex, race, and socioeconomic status, as well as its influence on prognosis and survival rate.
随着人工智能(AI)辅助诊断的广泛普及,考虑其在全球范围内报告的 2018 年超过 180 万例和 88.1 万人死亡的结直肠癌(CRC)早期诊断中的效用和效率变得至关重要。AI 辅助结肠镜检查(AIC)在提高腺瘤检出率以及更好地对息肉进行特征描述方面具有显著优势。本系统评价(SR)研究了与传统结肠镜相比,AIC 在 CRC 早期诊断中的效果。
在 2017 年至 2022 年期间,使用广泛的搜索策略,通过医学主题词在电子数据库(PubMed/Medline、SCOPUS 和 Web of Science)中检索了原始研究(随机对照试验、观察性研究)、SR 和荟萃分析。所有搜索均根据系统评价和荟萃分析的 Preferred Reporting Items 进行,并于 2022 年 11 月进行分析。使用基于 Cochrane 消费者和传播评论组的质量评估和证据综合提取模板的数据提取表进行数据提取。所有纳入的研究均经过偏倚和伦理标准的考虑,并提供了有价值的证据来回答研究问题。
数据库搜索共确定了 218 篇研究,其中 87 篇来自 PubMed,60 篇来自 SCOPUS,71 篇来自 Web of Science 数据库。从数据库中检索到的研究被导入 Rayyan 软件,并进行了重复文章检查,在仔细评估数据后删除了所有重复文章。根据以下纳入标准进行了摘要和全文筛选:观察性研究采用 STROBE(Strengthening the Reporting of Observational Studies in Epidemiology);综述采用 PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analysis);叙述性研究采用 ENTREQ(Enhancing the QUAlity and Transparency Of health Research);随机对照试验采用改良 Jadad 量表。这产生了 15 项符合本 SR 要求的研究,并最终纳入综述。
与传统结肠镜相比,AIC 是一种安全、高效的筛查工具,可提高腺瘤和息肉的检出率,从而有助于成年人 CRC 的早期诊断。本 SR 的结果提示需要进一步开展大规模研究,以调查其在性别、种族和社会经济地位方面的有效性,以及对预后和生存率的影响。